The dataset has 7 mixtures, 8 dilutions, two replicates and 5 common control controls. Four observations are missing, giving a total of 113 observations.

data(glymet)

Format

A data frame with 113 observations on the following 3 variables.

dose

a numeric vector of dose values

pct

a numeric vector denoting the grouping according to the mixtures percentages

rgr

a numeric vector of response values (relative growth rates)

Details

The dataset is analysed in Soerensen et al (2007). The concentration addition model can be entertained for this dataset.

Source

The dataset is kindly provided by Nina Cedergreen, Department of Agricultural Sciences, Royal Veterinary and Agricultural University, Denmark.

References

Soerensen, H. and Cedergreen, N. and Skovgaard, I. M. and Streibig, J. C. (2007) An isobole-based statistical model and test for synergism/antagonism in binary mixture toxicity experiments, Environmental and Ecological Statistics, 14, 383--397.

Examples

# NOT RUN {
library(drc)

## Fitting the model with freely varying ED50 values
glymet.free <- drm(rgr~dose, pct, data = glymet,
fct = LL.3(), pmodels = list(~factor(pct) , ~1, ~factor(pct)))

## Lack-of-fit test
modelFit(glymet.free)  # acceptable
summary(glymet.free)

## Plotting isobole structure
isobole(glymet.free, exchange=0.01)

## Fitting the concentration addition model
glymet.ca <- mixture(glymet.free, model = "CA")

## Comparing to model with freely varying e parameter
anova(glymet.ca, glymet.free)  # borderline accepted

## Plotting isobole based on concentration addition
isobole(glymet.free, glymet.ca, exchange = 0.01)  # acceptable fit

## Fitting the Hewlett model
glymet.hew <- mixture(glymet.free, model = "Hewlett")

### Comparing to model with freely varying e parameter
anova(glymet.ca, glymet.hew)
# borderline accepted
# the Hewlett model offers no improvement over concentration addition

## Plotting isobole based on the Hewlett model
isobole(glymet.free, glymet.hew, exchange = 0.01)
# no improvement over concentration addition
# }